discretize.tests.get_quadratic#
- discretize.tests.get_quadratic(A, b, c=0)[source]#
Return a function that evaluates the given quadratic.
Given A, b and c, this returns a function that evaluates the quadratic for a vector x. Where \(\mathbf{A} \in \mathbb{R}^{NxN}\), \(\mathbf{b} \in \mathbb{R}^N\) and \(c\) is a constant, this function evaluates the following quadratic:
\[Q( \mathbf{x} ) = \frac{1}{2} \mathbf{x^T A x + b^T x} + c\]for a vector \(\mathbf{x}\). It also optionally returns the gradient of the above equation, and its Hessian.
- Parameters:
- A(
N
,N
)numpy.ndarray
A square matrix
- b(
N
)numpy.ndarray
A vector
- c
float
A constant
- A(
- Returns:
function
The callable function that returns the quadratic evaluation, and optionally its gradient, and Hessian.